At a minimum, they are examples of environmental technologies that predate the rise of sustainability and widespread environmental awareness in landscape architecture. They also suggest a rich legacy of technological innovation born from the same environmental pragmatism and innovation that define contemporary landscape architecture. It is humbling to think that 30-plus years before the word “sustainability” found its current usage in environmental fields and the language more broadly, a tinkerer in New Jersey invented a permeable turf paver in 1940 through which the “roots of seedlings may take root, and thereby provide an interlocking connection between adjoining blocks.” Or that an inventor in Mahopac, New York, had the prescience in 1932 to devise a technique for anchoring trees to buildings and structures 80 years before they adorned the Bosco Verticale in Milan . Or that an early innovator in the geotechnical arts integrated the process of decomposition into a slope stabilization system in 1933, many years before ideas of weathering became common to landscape practice. These inventions provide us with important antecedents to the word “sustainability” and challenge landscape architects to reevaluate the relationship among innovation, early adoption of technology, professional practice, academic research, and implementation in the built environment. One of the most important figures in the history of innovation in landscape-related technologies is Stanley Hart White, a professor of landscape architecture at the University of Illinois from 1922 to 1959. White patented the first known vertical garden in 1938, roll bench yet the idea emerged in his writings and sketches as far back as 1931 .

His technology integrated a steel structural framework with hydroponic substrate, internal irrigation, and vegetation to provide fine sheets of greenery as a background and camouflage for the modern garden. White prototyped the “Vegetation-Bearing Architectonic Structure and System” in his Urbana garden shed more than 60 years before the emergence of the vertical garden in the contemporary built environment.The merits of this invention may ultimately pale in comparison to the precedent he established for a landscape architect-cum-inventor and technological innovator. White translated modern landscape theory, advances in building sciences, and emergent hydroponics into patent legalese, formulating the origins of vegetation-bearing architecture and pioneering green modernism. At that moment, landscape theory and technology converged at a 1:1 scale. It is hard to recall an instance in the annals of history when the vanguard of landscape thinking intersected so narrowly with the reification of technology, making White’s simultaneous commitment to theory and technology important beyond the invention of the vertical garden. What is the relationship between landscape architecture and technology? Are we simply purveyors and consumers legally chartered to select and specify the next best ready-made in construction documents? Is our use of computers for drawing, mapping, or rendering of future scenarios akin to true invention? Do we have a legacy of inventors and tinkerers who reify, curate, and improve the technologies that materialize our future sustainable and ecological cities? These questions are existential, as progress toward sustainable, ecological, and equitable future landscapes is in part technological determinism at work . Whoever develops the technology that leads us forward in these realms determines, in part, the future configuration of our cities and broader society. Currently, innovation in landscape-related technology is primarily the task of disciplines tangentially oriented to landscape architecture such as material sciences, industrial design, computer science, geotechnical and civil engineering, horticulture, furniture manufacturing, fabrication, and others concerned with the technical, material, and tectonic dimensions of landscape systems. Isn’t this the scope of landscape architecture? I believe it is! The patent archive now boasts thousands of landscape-related technologies, from Subsurface Upflow Wetland Systems to Reinforced Slope Planting Structures and Segmental Bio-retention Basin Systems .

Innovation in this sector will continue to thrive; the question is whether or not landscape architects will lead the way. P. vulgaris is characterized by a particular evolutionary history. Recent analyses based on sequence data presented clear evidence of the Mesoamerican origin of common bean, which was most likely located in México . The expansion of this species to South America resulted in the development of two ecogeographic distinct genetic pools with partial reproductive isolation . After the formation of these genetic pools -between 500,000 and 100,000 years ago – domestication took place, independently in the Mesoamerican and the southern Andean regions of the American continent . Genome analysis of BAT93 and G19833 , P. vulgaris sequenced model genotypes, has initially revealed interesting differences, for example between their genome size and number of annotated genes . The common bean is the most important legume for human consumption. In less favored countries from Latin America and Africa, common bean are staple crops serving as the primary source of protein in the diet. Soil acidity in these tropical regions is a major constraint for crop productivity, usually resulting in a combination of nutrient deficiency and metal toxicity . In acidic soils, aluminum toxicity is the primary factor of growth restriction, resulting in the inhibition of root growth and function, as well as in the increased risk of plants to perish of drought and mineral deficiencies, thus decreasing crop production.In Arabidopsis, the regulation of root growth is modulated by an ABC transporter‐like protein, annotated as ALUMINUM SENSITIVE PROTEIN 3 , which is localized in the tonoplast, suggesting a role in Al vacuolar sequestration . The LOW PHOSPHATE ROOT 1 ferroxidase, an ALS3– downstream protein of the phosphate-deficiency signaling pathway, is involved in root growth inhibition, by modulating iron homeostasis and ROS accumulation in root apical meristem and elongation zone . In root cells, AlT can affect multiple areas, as the plasma membrane, the cell wall and symplastic components . Common bean is known to be highly sensitive to AlT but this sensitivity is genotype-dependent .

In 2010, the evaluation of the root morphological traits related to AlT of 36 P. vulgaris genotypes revealed that Andean genotypes were more resistant to Al than Mesoamerican ones . Mendoza-Soto et al. reported that Mesoamerican common-bean plants subjected to high Al levels for short periods showed decreased root length as well as characteristic symptoms of AlT, such as ROS accumulation, callose deposition, lipoperoxidation and cell death in roots. Along other regulators, plant response to metal toxicity involves also microRNAs as part of the regulatory mechanisms. These molecules are a class of non-coding small RNAs of about 21 nucleotides in length, regulating gene expression at post-transcriptional level, guided by sequence complementarity, inducing cleavage or translational inhibition of the corresponding target transcript . The relevance of miRNA regulation in heavy metal tolerance is well documented; it has been demonstrated that heavy metal-responsive miRNAs show differential expression according to the toxicity level. Target genes of these miRNAs generally encode transcription factors that transcriptionally regulate networks relevant for the response to heavy metals. Additionally these encode transcripts for proteins that participate in metal absorption and transport, protein folding, antioxidant system, phytohormone signaling, or miRNA biogenesis and feedback regulation . High-throughput small RNA sequencing analyses have identified miRNAs that respond to AlT in roots of different plants species, however their function in response to AlT is largely unknown. Some of the target genes cleaved by AlT-responsive miRNAs encode disease resistance proteins, transcription factors or auxin signaling proteins . Our previous research indicated that P. vulgaris is no exception to this phenomenon. We identified common-bean miRNAs that respond to Al,commercial greenhouse supplies these include conserved miRNAs that are Al-responsive in other plant species -i.e. miR319, miR390, miR393- and also miR1511 . miRNAs from the miR1511 family have been identified in non-legume plants like strawberry  and poplar tree , although in the latter its nature as a miRNA has been discussed as it has been considered as part of a retrotransposon . Regarding legumes, miR1511 has been identified in Medicago truncatula and soybean . Also, miR1511 was identified in Mesoamerican common-bean cultivars, being more abundant in flowers and roots . However, this miRNA was not identified when analyzing the Andean G19833 reference genome . Genetic variation in MIR1511 has been reported in a comparative genotyping analysis of different Asian accession of domesticated soybean as well as its wild type progenitor Glycine soja. While sequences of mature miR1511 and miR1511* were found in G. max accessions, the sequences of annual wild G. soja showed insertion/deletion in the stem-loop region of MIR1511 that included complete or partial deletions of mature miR1511 sequence . Updated research indicates that the miR1511 target gene is not conserved in the different plants where it has been identified. In strawberry, the miR1511 targets an LTR retrotransposon gene . Inconsistencies about the nature of miR1511 target gene also hold for legume species. For instance, different targets have been proposed for soybean ranging from genes coding for proteins involved in the regulation of nitrogen metabolism to proteins relevant in plant cell development .

While in other species such as M. truncatula target genes have been searched but have not been identified. The SP1L1 transcript has been proposed as the common-bean miR1511 target , however despite several efforts from our and other groups this prediction could not be experimentally validated. These results suggested a species-specific selection of the corresponding target thus it was essential to experimentally validate the nature and possible function of the miR1511 target gene in common bean. Recent analyses led us to predict an ABC-2-type transporter-related gene, annotated as Aluminum Sensitive Protein 3 , as the target for miR1511. In this work we present its experimental validation. In addition, we genotyped MIR1511 in ecogeographically different common-bean cultivars and investigated the role of miR1511 and its corresponding target in the regulation of plant response to AlT. The comparison of MIR1511 sequence from BAT93 vs. G19833 P. vulgaris reference sequences showed a 58-bp deletion in the G19833 genotype. Such deletion comprised around 57% of pre-miR1511 sequence and included 7-bp and 10-bp of mature and star miR1511, respectively . To explore this phenomenon at a larger scale within the Phaseolus genus, we analyzed Genotyping-By-Sequencing data from 87 genotypes originated from a single genetic population , called non-admixed genotypes. These included genotypes from three Phaseolus species and different populations of wild P. vulgaris: three populations from the Mesoamerican , one from the Andean , and one from the Northern Peru–Ecuador gene pools . All the genotypes belonging to the Andean gene pool and part of the Mesoamerican genotypes displayed a truncated MIR1511, in contrast to the Northern Peru– Ecuador genotypes and the other Phaseolus species that presented a complete version of the MIR1511 in their genome. A population clustering of P. vulgaris genotypes confirmed these results and showed that in the three Mesoamerican populations only a part of the MW1 cluster presented the MIR1511 deletion . Predicted target genes for P. vulgaris miR1511 include SP1L1-like  and isopentyl-diphosphate delta-isomerase , previously reported , and a protein with unknown function and the Aluminum Sensitive Protein 3 , from our recent bio-informatic analysis. From these predicted targets, ALS3 is the only one possibly related to AlT, as reported for Arabidopsis , and showing an adequate binding-site penalty score , thus the 5’RLM-RACE assay was used to experimentally validate the ALS3 mRNA cleavage site. As shown in Figure 3a, a significant number independently cloned transcripts mapped to the predicted site of cleavage, between the nucleotides at positions 457 and 458 of the transcript, which corresponds to position 9 and 10 of the predicted miR1511 binding site, thus confirming a miR1511-induced degradation. The other two degradation events mapped to 7 nucleotides upstream and 17 nucleotides downstream of the miRNA-associated degradation site, suggesting random degradation. An additional action of miR1511 to induce translation inhibition of ALS3 mRNA in common bean, cannot be excluded. miR1511 target genes differ among plant species . In order to evaluate the specificity of the miR1511/ALS3 regulatory node in common bean, we analyzed the miR1511/ALS3 binding site sequence alignment from eight model plant species, including five legumes, which contain a precursor gene of miR1511 in their genome . Because of the deletion in MIR1511 from the G19833 genotype, we used the mature miR1511 and the corresponding ALS3 binding site sequences from the BAT93 Mesoamerican genotype, as representative of P. vulgaris.

An agro-economic approach examines the effect on crop productivity of experimentally controlled changes in water, temperature and other possible influences on yield, such as soil characteristics. This approach is, however, subject to the criticism that it overlooks adaptations or adjustments that farmers might make to changes in climate variable – for example, changing the crop mix to something more suited to the new conditions. Recent work in this area has tried to allow for this sort of adjustment. It is possible to use existing variation, across regions down to the county level in the U.S., in temperature, precipitation, soil quality and so on, to estimate a relationship between agricultural land value, on the one hand, and these input variables on the other. Presumably farmers have adjusted their crop choices to reflect long run climate and other differences in different areas. The estimated relationship can then be used to predict the impact on farmland value of projected future changes in the climate variables, holding constant other influences on value such as soil quality, and even socioeconomic variables such as population and income level in a county. When this is done, researchers have found that the likely impact of the temperature and precipitation changes associated with a doubling of atmospheric concentrations of greenhouse gases, principally carbon dioxide from the combustion of fossil fuels, on the value of farmland in the U.S. is quite modest, and may even be positive. One recent study summarizing and reviewing work in this area concludes that the warming associated with a doubling of atmospheric concentrations of greenhouse gases will result in a net gain of $8.4 billion annually for the U.S. economy, with the largest component a benefit to agriculture of $11.3 billion . I am currently engaged in work with my colleague, Michael Hanemann, and graduate student, Wolfram Schlenker,round plastic pots to adopt the econometric or statistical approach of relating farmland value to climate and other influences. We come to strikingly different conclusions.

Precipitation during the growing season is virtually nonexistent. Yet California agriculture is profitable, and the value of farmland here is quite high relative to other areas. The explanation, of course, is that crop yields are not related to precipitation during the growing season. Instead, they depend on irrigation, from stored ground or surface water. For surface water especially, what matters is how much snow falls in the Sierras, and when it melts and runs off into streams that feed the large surface reservoirs that in turn supply local irrigation districts. A statistical analysis that simply relates local precipitation to local crop yields, or the value of local cropland, may – and has – come to the misleading conclusion that the relationship between precipitation and value is negative, since in California and the arid west generally some very high-valued farmland receives little or no rainfall during the growing season.Consider a scenario in which over the next several decades the atmospheric concentration of greenhouse gases doubles, and average temperature in the U.S. rises by about five degrees Fahrenheit . To compensate for the higher temperatures, farmers in areas without irrigation would invest in irrigation facilities, as was done earlier in California and elsewhere. Proponents of the econometric approach might argue – indeed, have argued – that this is taken into account in the estimated relationships. Currently irrigated farmland has a high value because the investment in irrigation was profitable, and was undertaken for that reason, as were other adjustments to climate. This is true, but is misleading as a guide to the impact of future warming. The difficulty is that existing irrigation facilities have been heavily subsidized. For example, in California it has been estimated that even after decades of operation, farmers have paid just 18% of the capital, operations and maintenance cost of the federal Central Valley Project. It is clear that, at a minimum, subsidies of this magnitude to agricultural water users – which have in the past been capitalized into the value of the land – are unlikely to be forthcoming in the future, due to changes in what we might call the fiscal climate.

Apart from the issue of subsidies, it appears that irrigation water will be more expensive in the future than it has been in the past. Again drawing on the California experience, the State Water Project delivers water from a storage and conveyance system constructed in the 1960s to irrigation districts in the Tulare Lake Basin at a wholesale cost of about $80 per acre-foot. However, the State Water Project has only about 60% of the supply capacity originally planned in 1960. If the system were now completed, current estimates are that the new water would cost on the order of $300-$450 per acre-foot. For both reasons, cost increases and reduced subsidies, the net benefit, as reflected in the value of agricultural land, from the construction of new irrigation facilities, is likely to be much less than what can be inferred from a statistical study that reflects historic costs and subsidies.One way to proceed, in these circumstances, is to do the statistical analysis on just areas of rainfed, as opposed to irrigated, agriculture. For the U.S., this involves nearly 80% of the counties , so there is no shortage of observations. When we do this, we find that the estimated relationship between precipitation during the growing season and farmland value is no longer negative. With the costless, or very low cost, option of irrigation out of the picture, the effect on farmland value is unambiguously negative. Under various different weighting schemes for the individual county observations, undertaken for technical reasons, the distribution of damages associated with a doubling of the atmospheric concentration of greenhouse gases converges around a median figure of $215 billion. This is the estimated loss in value of agricultural land. Assuming a real interest rate of 5%, this translates into an annual loss of just under $11 billion, as compared to the previous estimate, noted above, of an annual net gain of just over $11 billion. The $11 billion loss estimate needs to be qualified, or at least further interpreted. To derive an estimate for the U.S. as a whole, the impact of warming on irrigated areas, prominently including California, must be added back in. If this is positive, the loss to U.S. agriculture as a whole would be reduced, perhaps even transformed into a net benefit, as in the earlier estimate.

Research we are undertaking for California suggests that this will not be the case. Warming is expected to lead to changes in the pattern of precipitation that will have a negative impact on agriculture in the state, apart from any impact due directly to temperature. The mix of rain and snow, during the winter rainy season, will shift to somewhat more rain, and less snow, than under present conditions. The snow that does fall in the Sierras will melt and run off somewhat earlier in the year. Thus less water will be flowing into the reservoirs, and available for agriculture – and other uses – when demand is highest, in the late spring and summer. On the other hand, winter rain and early spring snow pack runoff into the reservoirs can be expected to exacerbate flooding, much as in the winter of 1997 when an unusually warm storm system moving through the state dumped heavy rains, rather than snow, in the mountains and resulted in major flooding up and down the Central Valley. Adding in an estimate of the impact of warming on existing irrigated areas in the U.S. is thus unlikely to reduce the $12 billion in losses estimated for non-irrigated areas, much less to convert the losses to gains. Another qualification to the results does however suggest that they may overstate the magnitude of potential losses from warming, and also has implications for policy. By excluding irrigation as an option in areas currently without it, we do not allow for the possibility that the cost of construction and operation of new irrigation infra- structure may be less than the losses otherwise suffered. Clearly it is not appropriate to assume that new irrigation will be forthcoming at historic costs, and under historic subsidies, but it is certainly possible that in some areas at least the full cost will be less than the losses without it. This is a question to be investigated on a region specific,hydroponic bucket indeed a project-specific, basis. What is indicated is a benefit/cost analysis of new water projects, where the benefit is the loss in value to agriculture and other sectors predicted to result without the project.Trade Commission jointly administer AD and CVD law . The DOC first determines whether a commodity is being dumped or subsidized and then the USITC decides whether or not the U.S. industry has been injured as a result. The DOC procedure is much less transparent than the USITC procedure. Although it seems too amazing to be true, the DOC rules in favor of the U.S. industry in 95% of the cases. The safeguard law is jointly administered by the USITC and by the President in that the USITC determines whether injury has resulted to the domestic industry and then issues a recommendation to the President for no relief or for a specific method of relief. The President then decides whether or not to heed the recommendation of the USITC or to choose an alternative method or no method for relief. Many other countries have trade remedy laws that are very similar to those in the United States. Traditionally, the United States, EU, Australia and Canada have filed the most AD and CVD cases against foreign suppliers, but more recently, developing countries have filed a growing number of cases.

In the past few years, developing countries have filed about 50% of the total number of AD and CVD cases worldwide. Economists generally view AD and CVD laws as nothing more than disguised protectionism that is used to protect domestic industries from foreign competition. As traditional trade barriers are lowered, the use of AD and CVD cases has risen worldwide. The main reason that developing countries have criticized the use of AD and CVD laws in developed countries, is their growing frustration with the protectionist use of these laws. For instance, Brazil was reluctant to fully engage itself in discussions on the Free Trade Area of the Americas because of the continued application of U.S. AD duties on products such as orange juice. This past summer, the filing of AD cases on their exports of raspberries and spring table grapes to the United States troubled Chile. It was no surprise that the U.S. grape and raspberry industries filed their cases while the negotiations for the Chile FTA were in full swing. More recently, U.S. honey producers have also received AD protection from competition from Argentina and China, as well as CVD protection from Argentina, which has certainly come at an inopportune time for Argentine producers. During the 1980 to 2000 time period, over 1300 AD and CVD cases were filed in the U.S., of which approximately 116 were agricultural cases. This means that agriculture has initiated its fair share of cases, because agriculture’s share of the value of U.S. total imports is only about 4%. Import relief law was used less often, as there were only 30 such total cases filed from 1980 to 2000. However, U.S. agriculture filed 8 of these 30 cases, and thus accounted for a rather large share. During this time period, there was no noticeable trend in either overall usage or agricultural usage of AD and CVD law. The outcome of the AD and CVD agricultural cases since 1980 is reported in Table 2, where we note that 41 of the 116 total cases resulted in an affirmative ruling in favor of the U.S. domestic industry. During the past two decades, Canada has been the largest target of U.S. AD and CVD agricultural cases. Apart from Canada, most cases have been filed against developing countries, such as China, Colombia and Mexico. As traditional forms of agricultural trade protection are reduced through the WTO, there will most likely be a growing number of trade remedy cases filed by U.S. agriculture. This will not only obstruct U.S. imports but will also encourage retaliation and increased protectionism in other countries. This is all the more reason to keep trade remedy laws on the WTO negotiating table.

Our critical review of the range and reliability of methods for estimating plant-soil BCR offers insight for environmental scientists who must interpret and apply plant-uptake estimates obtained from models and experiments. In this assessment we have emphasized the importance of confronting uncertainties at each stage of the model development and application. We see that uncertainty emerges at the conceptual model stage as well as during mathematical model formulation and calibration and in model applications. The results above show that uncertainty is not simply a variance propagation or “Monte Carlo” assessment that is used to propagate parameter variance at the model application stage. Instead it is a process that begins at the earliest stage of model development and accrues through model formulation and specific applications. In the studies reviewed in this paper, we find that important uncertainties arise at the first stage of model development—the concept formulation. For plant uptake models that address competing soil-root-leaf and soil-air-leaf pathways, conceptual uncertainties remain a dominant source of overall uncertainty. An important contributor to this conceptual uncertainty is the lack of a consistent definition of BCR for soil uptake in both experiments and models. This leads to confusion and inconsistency in the use of BCR. Because this type of uncertainty is difficult, if not impossible, to quantify, we must develop qualitative methods and classifications to communicate this important source of uncertainty. In evaluating model formulation, we observe large differences among models in their predictions of BCR,livestock fodder system but we discovered no clear basis for selecting one model as more accurate than another. The residual errors reported for many of the models in fitting their calibration data leads us to believe that we do not yet have sufficient data to formulate accurate models. But our review of experiments for the single chemical RDX reveals that much of the uncertainty is attributable to the lack of precision and variability of experimental data used to obtain the BCR values used to calibrate models.

It appears that there are advantages to using more than one compartment in formulating BCR models. But lack of experimental data and the poor state of conceptual knowledge suggests that model uncertainty cannot be reduced by adding large numbers of compartments to the models. Too many plant components in our models lead to over specification. But a single compartment model can miss the combined effect of root and shoot uptake processes. The interaction among measurements, conceptual models, and models leads to the conclusion, contrary to our initial expectation, that it may not be possible to distinguish the relative contributions of overall uncertainty from conceptual uncertainty, measurement variability, and model uncertainty. For example, the variations in the value of BCR obtained from the 81 experiments we considered for RDX span a rather wide range. But it is not clear how much of this variation is attributable to experimental uncertainty and how much to inadequate conceptual models. Often the conceptual model is used to design experiments so that an incorrect conceptual model leads to measurements that are difficult to interpret when they are inconsistent with the concept. Perhaps the variance in the experimental values would be much lower if we understood better how BCR is affected by variables whose impact is not yet fully understood—for example temperature, soil properties, etc. Similarly if we really had a complete and thorough conceptual understanding of the process of uptake, then choosing a mathematical equation would likely be less uncertain. That is, the mathematical model formulation may only appear uncertain because we are using mostly-empirical mathematical relationships to describe a process that we do not understand well enough at a conceptual level. So it is not clear whether we classify this as uncertainty in the mathematical model formulation, or as uncertainty in the conceptual model. In applying model performance evaluation to plant uptake modeling, the results and discussion above lead us to a number of key findings. These include: The conceptual formulation of the bio-concentration ratio has an important, but at this point difficult to quantify, contribution to overall uncertainty. In particular, the concept of different plant components, the selection of dry- versus fresh-mass concentrations, and the use of dynamic or steady state concentration ratio strongly impact the reliability and uncertainty of the resulting BCR model.

When we consider both the performance of models with respect to their calibration experiments and also compare different models, we find that quantitative results for any randomly selected organic chemical have very large model uncertainties. We estimate that in the absence of specific experimental information, the expected uncertainty of a BCR model can be represented by a log normal distribution with a GSD of 10 . This means that without additional information on plant species or without plant- and site- specific measurements, we can only expect a model to predict a BCR within ±1 log units such that there is a 66% likelihood that the actual BCR value is 10 times higher or lower than the value obtained from a model. Based on consideration of a large number of experiments for a single, well-studied compound, RDX, we find that experimental measurements of BCR have large experimental variability and that this experimental variability can be represented by a log normal distribution with a GSD of 3.5 . This indicates much of our observed model uncertainty most likely derives from experimental variability. This leads to the observation that controlled measurements cannot necessarily remove the large uncertainties that derive from BCR models. Comparison for RDX of the relative contributions of model uncertainty and experimental variability to uncertainty in BCR estimates indicates that a large fraction of model uncertainty can be attributed to experimental variability. The variability and complexity of the uptake and transport of chemicals in vegetation cannot be captured by a point-value for BCF, but requires the use of ranges and confidence intervals to communicate the large uncertainties associated with estimating BCRs. In any plant-uptake model used to estimate a BCR, we must develop a process for communicating both the magnitude of the result and the confidence that can be placed in this number. On the part of the assessor this requires a presentation of both qualitative and quantitative uncertainties. Heavy metals such as iron , zinc , copper , and manganese are essential micro-nutrients for all organisms, acting as co-factors in a variety of biological processes. These heavy metals are extremely reactive and can become toxic at high concentrations; therefore, the intracellular concentration of these essential metals must be tightly regulated . Other heavy metals such as cadmium , lead, mercury, and the metalloid arsenic do not have biological functions in plants and are toxic even in trace amounts, disrupting several biochemical activities by displacing essential metals from their respective binding sites .

In humans, Cd exposure has been linked to cancer in the kidneys, lungs, and prostate, and severe Cd poisonings can result in neurological disorders and pulmonary and renal failure . While occupational exposure and tobacco products are associated with a high risk of Cd poisoning, consumption of contaminated plant-based foods represents the major source of Cd exposure in the general public . Many cases of widespread cadmium poisonings have been attributed to consumption of contaminated seeds in Thailand, China, Japan, and Australia . However, the molecular mechanisms and genes mediating the loading of both essential and nonessential heavy metals into seeds remain largely unknown. Metal accumulation and distribution in plants consist of several mechanisms, including: metal uptake into roots, xylem-loading and transport to the shoot, and phloem-mediated redistribution of metals from mature leaves to sink tissues, including younger leaves, roots, and seeds . Cadmium enters the root through the Fe transporter IRT1, which shows broad substrate specificity towards divalent metals including Fe2+, Zn2+, Mn2+, and Cd2+ . Once inside the cell, metals bind to different ligands, according to specific affinities, and these metal–ligand complexes can be stored in different cellular compartments or distributed to other tissues through the vasculature . Because of the broad substrate specificity of IRT1 for divalent metals, transcriptional regulation of the Fe-deficiency response,fodder system trays including up-regulation of IRT1, will also have an impact on the uptake of non-essential heavy metals such as Cd. In plants, the root iron-deficiency response is regulated by local signals within the root and also by systemic signals originating from leaves . Two major transcriptional networks have been identified to mediate the Fe-deficiency response at the root level in Arabidopsis: the FIT network and the POPEYE network .The identification of mutants showing a constitutive Fe-deficiency response even when Fe is supplied in sufficient amounts plus experiments where the constitutive root response is restored by foliar application of Fe suggest that mobile Fe is required for proper shoot-to-root signaling . However, the transporters, ligands, and the chemical speciation of the putative phloem-mobile molecule mediating the systemic Fe signaling have not yet been clearly identified. Here, we report that opt3-2, an Arabidopsis mutant carrying an insertion in the 5’ UTR of the oligopeptide transporter gene OPT3 , over-accumulates significant levels of Cd in seeds. We present evidence suggesting that this Cd over-accumulation may be the result of an enhanced transport of Cd through the plant, making opt3-2 a suitable background for studying long-distance transport of non-essential heavy metals. We further show that OPT3 is targeted to the plasma membrane and is preferentially expressed in the phloem.

The Fe/Zn/Mn uptake transporter IRT1 and other ironstarvation-induced genes are constitutively up-regulated in opt3-2. Interestingly, shoot-specific expression of OPT3 restores metal homeostasis and IRT1 up-regulation in roots showing that OPT3 is the first identified molecular component of the network transferring information on the iron status from leaves to roots. Moreover, Fe mobilization between leaves is impaired in opt3-2, suggesting that OPT3 mediates the movement of Fe out of the leaves, and this transport is required for proper communication between leaves and roots and maintenance of the trace-metal homeostasis in Arabidopsis. Understanding phloem-mediated signaling, transport, and seed-loading mechanisms of both essential and non-essential heavy metals will help to develop strategies for excluding toxic metals from seeds and enhance the nutritional value of grains and plant-based products.Members of the Arabidopsis oligopeptide transporter family have been shown to mediate the transport of a broad spectrum of peptides . Glutathione and phytochelatins are peptides that mediate tolerance and long-distance transport of heavy metals ; therefore, we screened mutants in the Arabidopsis OPT family for differential accumulation of Cd in seeds. A mutant of the Arabidopsis OPT3 gene, opt3-2, showed the strongest over-accumulation of Cd in seeds . To test whether this Cd over-accumulation had an effect on seedling growth, assays were performed on plates in the presence and absence of Cd. Figure 1B shows that opt3-2 is hypersensitive to Cd when grown on medium containing 50 μM CdCl2. To determine whether the increased Cd concentration in opt3-2 seeds was due to a systemic over accumulation of Cd throughout the plant, opt3-2 seedlings were grown hydroponically for 6 weeks, exposed to 20 μM CdCl2 for 72h and the metal concentration of roots and leaves was measured by ICP–OES . The roots of opt3-2 over-accumulated Cd compared to wild-type; however, unexpectedly, Cd concentrations in leaves were almost five-fold less than those of wild-type plants . Conversely, seeds of opt3-2 plants show a large increase in Cd levels compared to wild-type seeds .To determine whether the altered distribution of Cd in opt3-2 correlated with the distribution of essential metals in plant tissues, the levels of Zn, Fe, and Mn in opt3- 2 were also measured and compared to wild-type plants . No dramatic differences in the concentration of Zn and Mn in seeds were found between wild-type and opt3-2 . However, in contrast to Cd accumulation, opt3-2 over-accumulated significant levels of Zn and Fe in leaves compared to wild-type . In roots, the concentration of Fe, Zn, and Mn was increased in opt3-2 compared to wild-type . The different distribution of Cd in aerial parts of the plants suggests that the mechanisms mediating accumulation of metals in opt3-2 leaves is different for Cd compared to the essential metals Fe, Zn, and Mn.

However, due to the short lifetimes of PET radioisotopes, only short biological processes, such as photosynthesis, may be imaged. In contrast, single gamma-ray emitting radio tracers used in single photon emission computed tomography are typically metals and do not easily label organic molecules. However, many trace element metals are essential to a plant’s survival . An active area of plant research is studying hyper accumulation of metals in plants using a radioisotope of that metal; commonly studied metals include: Cd, Zn, Mn, Co, and Ni . Other potential applications for SPECT imaging include: studying plant ion transport in xylem , studying metabolic processes such as tracers for phloem transport , and studying signaling by labeled exogenous peptides or proteins . One further advantage of imaging systems based on gamma-ray detection is the possibility of detecting the interactions of multiple radioisotopes simultaneously as the gamma-rays that they emit have distinct energies that can be distinguished from each other by the detector. For example, simultaneous imaging of 65Zn and 109Cd would enable teasing apart the competition dynamics in their uptake. However, there is an inherent trade off in increased sensitivity of the UCD-SPI system with spatial resolution. Spatial resolution at the mm-scale could be obtained using a collimator to better define the spatial origin of detected gamma rays, but this would lead to a greatly reduced event rate in the system. For the high-energy gamma rays of 65Zn, collimation is a particular challenge. Given the hours-long time scale of the transport studied here, it is possible that the choice of a collimator could have provided improved event positioning while preserving a usable event rate. A possible hybrid approach could have included using an insertable/removable collimator to acquire an alternating combination of two types of images: high sensitivity-low spatial resolution without the collimator; and low sensitivity-higher spatial resolution with a collimator. However, led grow lights the use of a collimator for this system is unexplored thus far.Zn uptake into the symplast in the outer root layers and loading into the apoplastic xylem stream are well understood on molecular level.

However, the dynamics of symplastic movement and patterning of the radial transport have thus far only been modeled to elucidate the timescales of these events . After xylem loading, the mass flow-mediated movement of Zn into the shoot inside the xylem is expected to occur within 30 min in Arabidopsis, as previously shown for water and Cd in xylem sap . From previous SPECT imaging, we have shown that a pulse of radiolabelled pertechnetate moving in the xylem stream reaches the shoot apical meristem of a 2 week old sunflower already in 5 min . The rate-limiting step for root-to-shoot translocation of Zn was proposed to be xylem loading involving HMA4 transporters in both A. halleri and A. thaliana . The dynamics of root-to-shoot Zn flux, however, have so far remained unclear in different species and transgenic lines. Estimates of Zn translocation rates from root to shoot were first obtained by spectroscopy methods of ashed shoot tissues. Early work with metal hyper accumulator Noccaea caerulescens suggested that the speed of root-to-shoot Zn transport was between 20 and 60 hr . Recently, positron imaging of Zn uptake estimated the time for Zn root-to-panicle transport in dwarfed mature rice to be 5.3 hr . Here, we have produced the first Zn root-to-shoot imaging data for A. halleri using UCD-SPI. Zn accumulates within the shoot of A. halleri, consistent with its ability to hyperaccumulate Zn, different from the HMA4 RNAi line. The speed of Zn transport into the shoot in our data as observed with the smoothed standard error show clear shoot accumulation within 5–7 hr, respectively . These results are in line with previous reports for rice . This contrasts strongly with the faster speed of the other xylem-transported compounds, such as water in A. thaliana , Cd in A. halleriand pertechnetate in sunflower , all measured to reach the shoot in 30 min. It should be noted, however, that the experiments demonstrating water transport and Cd transport were carried out using decapitated stems and are thus destructive in nature, but also far more sensitive to small quantities than the method used here. The slower speed of Zn transport indicates that Zn loading into the xylem by HMA4 is slow and under tight control even in the metal hyper accumulator A. halleri. Modelling the radial transport of Zn uptake has indeed indicated that HMA concentration is one of the key determinants of the uptake dynamics . The HMA4 transporter pumps Zn2+ from the root symplasm into the apoplastic xylem sap of A. thaliana . Strongly elevated expression of A. halleri HMA4 was suggested to be responsible for the increased in root-to-shoot translocation of Zn in A. halleri relative to A. thaliana . This conclusion was drawn based on the quantification of shoot Zn concentrations after long-term growth in HMA4-RNAi lines and wild-type A. halleri and in A. thaliana Col-0 . In the same experiment, root Zn concentration was elevated in some A. halleri HMA4 RNAi lines relative to A. halleri wild-type plants and even relative to A. thaliana . HMA4 is critical to the ability of A. halleri to hyper accumulate Zn.

We tested the functional role of HMA4 for A. halleri Zn translocation from root to shoot by imaging the Zn uptake dynamics of A. halleri HMA4-RNAi line relative to A. halleri. We found that the Zn signal in the shoot of HMA4-RNAi line did not increase over our 40-hr imaging period, but conversely, we saw a continuous decrease in shoot Zn signal with significant differences observable at 3 hr . The lack of an increase in shoot Zn confirms that Zn loading into the xylem is abolished in the HMA4-RNAi plants . The continuous decrease in the Zn signal in the shoot ROI seems to reflect bleeding of the strong early Zn signal from the root ROI into the shoot ROI. The dissipating signal through the A. halleri HMA4- RNAi time course could be due to apoplastic 65Zn adsorbed to the cell walls of outer root layers during the 65Zn pulse and not removed by the triple rinsing with Hoagland solution. This cell wall-adsorbed 65Zn would be desorbed into the growth medium during the imaging period by diffusion. The influx of Zn into the root symplasm is very tightly and rapidly regulated in Zn-concentration dependent fashion . Without the loading of Zn into the xylem, Zn builds up in the root symplasm. In the case of A. halleri HMA4-RNAi, the symplasm could be saturated with Zn at 3 hr after the resupply, leading to prevention of further uptake of the cell wall-adsorbed 65Zn and thus higher Zn desorption than Zn uptake into the symplasm. Finally, we compared the dynamics of Zn movement in the Zn hyper accumulator A. halleri with those in the related species A. thaliana, a non-metal hyper accumulator. Based on previous studies comparing Zndeficient to Zn-sufficient plants of A. thaliana and/or A. halleri, the Zn concentrations in our hydroponic solutions can be estimated to result in moderate Zn deficiency . The net concentration of 65Zn in the resupply media over the 24 hr period showed a net decrease, suggesting that Zn was taken up into the shoot, although these levels are variable. We found that Zn resupply after Zn deprivation in A. thaliana did not lead to detectable uptake or change of Zn in the shoot or the root ROI. It is possible that the small size and flat rosette growth habit of A. thaliana affected our ability to detect Zn dynamics. Also, low abundance of HMA4 transporters in A. thaliana roots may lead to much slower dynamics that we were unable to capture. In the absence of quantification of 65Zn levels in the shoot, it is possible, although unlikely, that Zn was not translocated in A. thaliana.Although most plants prevent the accumulation of heavy metals so as to avert toxicity, metal hyper accumulators selectively extract high concentrations of metals from the soil into their shoots without incurring symptoms of toxicity . By using the heavy metal radio label 65Zn and the UCD-SPI imaging system, we gained a more detailed spatiotemporal understanding of the dynamics of metal movement into plants, which may be a path toward the use and understanding of metal hyper accumulating plants for such advantageous applications.Reading comprehension is a complex process that requires the coordination and integration of a number of component cognitive skills. The ability to read single words in isolation is widely accepted as one skill critical to comprehension, but successful reading comprehension does not always directly stem from adequate word identification skills. Some individuals who are skilled word readers are not skilled passage comprehenders , supporting the idea that reading comprehension requires processes above and beyond single word reading. Theoretical models of reading comprehension propose that successful comprehension requires a reader to draw on both text-based information and prior knowledge in order to build a coherent and meaningful mental representation of the text . This mental representation is the reader’s understanding of the text’s deeper meaning; it consists of ideas from the text,strawberry gutter system relevant background knowledge, and inferences the reader makes about things not explicitly stated in the text . Building this mental representation is a dynamic process because cognitive demands change over time. For example, readers are known to spend more time processing words and sentences at the beginning of a text relative to later points.

This could be due to the fact that, without context or relevant background knowledge activated to facilitate comprehension, comprehension necessitates more effortful attention to the initial construction of a mental representation . Conversely, later stages of comprehension processes are facilitated by an increasing semantic contextualization . A number of imaging studies have examined the neurobiological correlates of reading comprehension . Patterns of activation emerge when processing discourse that cannot be predicted from models of reading single words, or even single sentences, in isolation . Areas that consistently appear to be unique to processing narrative texts include the dorsal medial prefrontal cortex and bilateral temporal parietal junction, often attributed to social cognition required in story comprehension, bilateral temporal poles , which play a role in generating specific semantic associations in connected text, and posterior medial structures, including posterior cingulate cortex and precuneus , which have been associated with updates in and integration of the reader’s mental model . This demonstrates that reading connected text involves additional processes beyond the phonological, orthographic, semantic, and syntactic processes seen at the word and sentence level. Still, many questions regarding how readers form a coherent text representation remain unanswered. Only a handful of studies have examined how the neural correlates of discourse processing change over the temporal progression of the discourse . Of the few, Xu et al. used fMRI to compare the activation associated with reading the beginning of a story with the activation associated with reading the end of the story . They found that processing the story’s setting and initiating events resulted in strongly left lateralized activation, while processing the story’s outcome resulted in increased activation in right hemisphere perisylvian and extrasylvian regions thought to contribute to inference and contextualization of narrative .These right hemisphere regions have since been related to social cognition processes that may be narrative-specific . This study provides evidence that reading comprehension not only involves processes distinct from those required in single word reading, but also that comprehension demands can vary from point to point within a given text. Similarly, by modifying the cohesiveness of text Yarkoni et al. identified neural regions that showed linear increases in activation as a function of reading time. More specifically, they compared construction processes with maintenance processes . They found that regions in the posterior parietal cortex associated with visuospatial updating and attention are involved in the construction of a reader’s mental model, while perisylvian language areas were more involved in its maintenance. These studies support theoretical models that suggest that building a mental representation of text is a dynamic process in which the cognitive demands shift from one point in the text to the next. Nevertheless, it is important to note that all of the aforementioned fMRI studies on discourse processing have exclusively examined narrative texts; none to date have examined expository texts . However, event-related potential and behavioral studies suggest such genre distinctions are important. For example, Baretta et al. used ERP to distinguish between narrative and expository texts.

The legibility of the names was not as important as the way the surface became progressively dense over the weeks of writing them. Parker realized that the process was “like a record of the soil growing. It’s like when you make your own compost and put it into the soil: it just continues to grow. So this painting may never be finished.”Mechanical eradication of Arundo can be attempted in many different manners. The most frequently used method is the cutting of the above ground material, the plant’s tall stems. Another method of mechanical eradication is digging out the underground biomass, the rhizomes.The large amount of standing above ground biomass, up to 45 kg/m2 impedes the removal of the cut material, because the costs will be too high. The costs associated with the removal of the large biomass of the stems, has led to the use of “chippers” that will cut the stems into pieces of approximately 5 – 10 cm in situ. After these efforts, the chipped fragments are left in place. A small fraction of the fragments left behind after chipping will contain a meristem. The stem pieces of these fragments may have been left intact, or split lengthwise. In the second case the node at which the meristem at located will have been split as well. On many pieces with a meristem, the meristem itself may still be intact. These stem fragments might sprout and regenerate into new Arundo plants . If stems are not cut into small pieces, or removed after cutting, the tall, cut stems can be washed into the watershed during a flood event. This material can accumulate behind bridges and water control structures with possible consequences as described in the introduction.

Meristems on the stems can also sprout, and lead to the establishment of new stands of Arundo at the eradication project site, bato bucket or down river . A. donax stands have a high stem density. The outer stalks of dense stands will start to lean to the outside because the leaves produced during the growing season push the stems in the stand apart. After the initial leaning due to crowding, gravity will pull the tall outside stems almost horizontal . Throughout this report these outside hanging stems will be referred to as “hanging stems”. The horizontal orientation causes hormonal asymmetry in these stems. The main hormones involved are IAA , GA and ethylene . The unusual IAA and GA distributions cause the side shoots developing on these hanging stems, to grow vertically. IAA also plays an important role in plant root development , and may therefore have a stimulative effect on root emergence from the adventious shoot meristem on fragments that originated from hanging stems, that would be absent in stem fragments from upright stems. In a preliminary experiment comparing root emergence between stem fragments from hanging and upright stems, 38% of the hanging stem stem fragments developed roots, while none of the upright stem-stem fragments showed root emergence . These results indicated the need for further study into the possibility that new A. donax plants can regenerate from the stem fragments with shoot meristems that might be dispersed during mechanical Arundo removal efforts. In order to apply herbicides at that time that the rate of downward translocation of photosynthates and herbicide would be greatest, this time period has to be established. Carbohydrate distribution and translocation within indeterminate plants, such as Arundo, results from the balance between the supply of carbon compounds to and the nitrogen concentration in the different plant tissues. Carbon and nitrogen are the most important elements in plant tissues. Due to different diffusion rates of NO3 – and NH4 + in soil water versus that of CO2 in air, and differences in plant N and C uptake rates, plant growth will earlier become nitrogen limited than carbon limited. During plant development tissue nitrogen concentrations are diluted by plant growth , which is mainly based on the addition of carbohydrates to the tissues.

When plant growth becomes nitrogen limited, the tissue will maintain the minimum nitrogen content needed for the nucleic acids and proteins that maintain metabolic function. At this low tissue nitrogen content, there is not enough nitrogen in an individual cell to provide the nucleic acids and proteins to support the metabolism of two cells, therefore the cells cannot divide. This means that the tissue cannot grow anymore , until it receives a new supply of nitrogen. When plant tissues cannot grow due to nitrogen limitation, they cannot incorporate or store additional carbohydrates. This lower physiological limit of tissue nitrogen content, at which no more cell division or incorporation of carbon is possible, is called the critical nitrogen content of the tissue . The CNC is expressed on a carbon basis .The CNC can be determined for whole plants , and for the different functional tissues of the plant. Different plant parts perform different functions, and therefore have different minimum nitrogen requirements for metabolism maintenance. In previous research with the dicotyledonous storage root perennial Ipomoea batatas , it was determined that the most photosynthetically active tissues, the leaves, and the fibrous roots, which are involved in nutrient uptake, have the highest CNC of all vegetative plant tissues . The storage roots of I. batatas had a significantly lower CNC than any of the other Ipomoea tissues. The difference between the actual tissue nitrogen content and the CNC determines the capacity of these different plant tissues to incorporate or store carbohydrates. Tissues with nitrogen contents that are above the CNC can still incorporate or store carbohydrates. These tissues have a positive carbon sink strength . Photosynthetically active tissues that have reached their CNC will not incorporate the produced carbohydrates, because that would dilute the nitrogen content of these tissues below the CNC, and metabolism would be impaired. Instead, the photosynthetically active tissues deposit the produced carbohydrates in the phloem, which transports them to those tissues that still have the ability to incorporate or store carbohydrates .

This is how leaves, that because of their high CNC loose the ability to incorporate the photosynthates in their own tissues relatively early during the development of the plant, can still produce photosynthates and translocate them down to the reserve storage organs, such as I. batatas storage roots, which maintain their positive carbon sink strength, and tissue growth , the longest of all plant tissues, due to their low CNC.Regeneration from stem fragments starts with the growth of a new stem from the meristem. Root growth from the meristem always follows shoot growth, and not all meristems with shoots will grow roots. Therefore, rooting of the stem fragment was selected as the criteria of successful regeneration from a meristem on a stem fragment. The stem fragments were checked for rooting three times per week. Rooting success was calculated in percent of all meristems in the container. The speed with which rooting occurred was expressed is t50. That is the number of days needed for 50% of the total number of meristems that eventually would root in a container, to root. When a stem fragment had rooted, the diameter of the stem at the point of the meristem was determined,dutch bucket hydroponic to assess the effect of the relative age of the meristem on the speed with which they rooted. The effect of the temperature at the time of rooting was tested for hanging A. donax stem fragments at two times in the growing season. In April 1998, 32 stem fragments were randomly distributed over 4 containers with aerated nutrient solution each at 10 and 20 °C. The stem fragments were monitored every day for rooting. Rooting success was calculated in percent of all meristems in each individual container, and mean rooting percentages were calculated for the four replicate containers for each fragment type. The speed with which rooting occurred was expressed using t50. This experiment was repeated in April 1999 at 15, 17.5, and 22.5. A repeat 20 °C treatment was included in the 1999 experiment, to allow for comparison with the 1998 experiment. Rooting of Arundo donax stem fragments under controlled temperatures at different exogenous indole acetic acid concentrations. Hanging stems and upright stems of A. donax were collected along the Santa Ana River, in Riverside County, CA, every month from February, 1999 through May, 2000. Eighty meristem containing fragments of each stem type were cut and surface sterilized. Twenty replicate fragments each , were randomly assigned to a control and three different exogenous IAA treatment levels . The fragments were placed in individual culture tubes , that had been auto claved containing 15 ml of plant growth medium with 4.4 g/L MS salts, 2 g/L Gel Gro, and the assigned concentration of IAA .

Each stem fragment was placed with its lower end in the rooting medium and its meristem submerged but near the interface of the rooting medium and the air. The upper end of the stem fragment extended above the rooting medium. The tubes were placed in a climate-controlled chamber with a temperature/light regime of 14 h of 27 °C in the light, and 10 h of 15 °C in the dark. The rooting of the fragments in the tubes was monitored daily for 30 days. Rooting success was calculated as percent of all meristems at the different IAA concentrations. The speed with which rooting occurred was expressed for each month using the t50 for each IAA concentration and stem type combination. The remaining meristem containing fragments from the hanging and upright A. donax stems that were collected monthly to test the effect of exogenous IAA were stored in tap water in separate containers. The containers were placed in the growth chamber under the temperature and light regime described previously, and the water was aerated. After approximately 10 days, the meristems on the fragments had developed into shoots and roots. Three replicate samples of approximately 10 g of the new shoot material were harvested from the stem fragments of both the hanging and the upright stems, and placed on ice. For the extraction of endogenous IAA, the samples were dipped in grinding media , placed in glass tubes, and flash frozen in liquid nitrogen. The tissues were homogenized for 2 minutes in 20 ml grinding medium with an Omnimixer . The homogenates were incubated on a wrist action shaker for 20 minutes and filtered through micro-cloth. The filtered solution was centrifuged at 10,000 rpm in a JA-17 rotor, and the supernatant was saved. The tissue material on the filter and the centrifugation pellet were combined and incubated again in 10 ml grinding media, and the sample was filtered and centrifuged as before. The supernatants were combined and their volume was reduced to 1 ml using a speed vacuum evaporator at 37 C. The concentrated samples were centrifuged at 13,000 rpm for 10 minutes at 4 °C. The supernatants were filtered through a 2 µm syringe filter . The resulting tissue extracts were stored in 1.5 ml centrifuge tubes, and stored at -80 °C. For the HPLC, the extracts were eluted from a C18 reverse phase column with an analytical SB-18 guard column , with a gradient solution of 20-35% acetonitrile with 20 mM sodium acetate at a flow rate of 1.5 ml/min. The samples were monitored using a spectrofluorimeter detection system at an excitation wavelength of 280 ± 10 nm, and an emission wavelength of 350 ± 10 nm. The IAA peaks of the sample extracts were identified and quantified using 0.1 and 0.5 µM standard solutions.The critical nitrogen content of Arundo leaf tissue was determined in a hydroponics experiment. One hundred Arundo stem fragments were collected in June 1998 from the Santa Ana River near River Road in Riverside county. In the greenhouse, the stem fragments were placed in water for 2 weeks to allow for root and shoot growth. After two weeks, 48 young plants that sprouted from the meristems on the stem fragments were randomly selected for use in the experiment. Four stems were placed in each of eleven 120-liter plastic containers, that were filled with 100 L aerated, half strength Hoagland nutrient solution .

Columns VIII-IX introduce government consumption and total fertility; again the results match those of Table 7, though the coefficient on yield remains consistent but is no longer significant at the 10 percent level. Finally, just as in Table 7, Columns X-XI drop the government consumption variable and report a coefficient of 0.35, now significant at the 10 percent level and consistent in magnitude with Table 7. Overall, the results using a 10-year lag on yield remain highly consistent with the results in Table 7, though the statistical threshold for significance is not passed in two of the second stage specifications. Finally, Table 10 presents a NAVA growth framework using GMM instrumentation and finds similar agricultural productivity effects on value added in non-agriculture sectors. Column I runs difference GMM and finds that a 10-year lag on yield is associated with subsequent increases in non-agricultural value added per worker, significant just short of 5 percent levels. The coefficient of 0.1 suggests that a 0.5 ton increase in yields leads to a 5 percent higher non-agricultural labor productivity 10 years later, which translates to a 0.5 percentage point higher growth rate. Note that this magnitude lies between the fixed effects coefficients of 0.05-0.06 and the IV coefficients of 0.27- 0.37 in Table 6, adding support to the overall results. The specification in Column I passes the Sargan test for over identification of instruments with a p-value of 0.43. Column II employs the Blundell-Bond “system” GMM estimator, though this does not pass a Sargan test under any relevant specification, so we prefer to interpret only difference GMM specifications. Column III adds the fertilizer price instrument to the exogenous variables in the specification, and finds similar results to Column I. Again, the estimation passes a Sargan test, and the AR test is satisfied with a pvalue of 0.09. Our analysis documents the strong positive links between agronomic inputs—fertilizer, water and modern seeds—and cereal yields per hectare, even after a variety of controls are introduced. We employ a combination of fixed effect,gutter berries instrumental variable and Arellano-Bond GMM estimators to posit a causal economy-wide link between, first, input use and yields, and, second, yields and various measures of economic growth and structural change.

We construct a novel instrument exploiting the economic geography of fertilizer production, which together with global fertilizer price fluctuations allow us to study economic growth and structural change in a statistically causal framework. The cross-country substantiation of both agricultural yield production functions and their links to various dimensions of economic growth and structural change are novel empirically. Taking the coefficients from Table 4, a representative country with yields of 1 t/ha that introduces an input package to jump from, say, 15 kg/ha to 65 kg/ha of fertilizer use would be expected to see an average yield jump of 147-470 kg/ha; while increasing from 10 to 50 percent use of modern seed would be expected to increase yields by 480 kg/ha. On the economic growth side, the instrumental variable results suggest that boosting yields from 1.5 t/ha to 2.0 t/ha is linked to a range of 13 to 19 percent increase in income per capita, a 3.3 to 3.9 percentage point lower share of labor in agriculture five years later, and approximately 20 percent higher non-agricultural labor productivity after roughly one decade. The estimated effects are identified based on exogenous variation in fertilizer prices, and are robust to the inclusion of controls for investment and standard macroeconomic policy indicator variables. The results suggest that land productivity promotes growth both by supporting changing labor shares and by increasing total factor productivity. Regressions focused on marginal effects of individual variables are, of course, not intended to evaluate nonlinear outcomes guided by Leontief-style agricultural production functions and discontinuous policy functions, so the regression results might underestimate the potential effects of yields. The results might also be constrained by issues of heterogeneity in cross-country production functions . The evidence in this paper points to strong potential yield and growth effects resulting from policy efforts to support adoption of a green revolution-type package of inputs in economies with low agricultural productivity and a large share of the labor force still in agriculture. The results suggest a particularly strong role for fertilizer, which is highly consistent with field station agronomic evidence.

Fertilizer’s high private return on experimental plots and in the field suggests some sort of market failure that policy can address; scholars debate whether the failure is due to credit constraints or non-rational behavior on the part of farmers . Regardless, the evidence presented in this paper suggests social returns from fertilizer use that exceed the immediate private returns, furthering the case for policy efforts. It is worth briefly describing the main concerns about increasing fertilizer use. One set is environmental. These are legitimate and require foresight in policy planning, but as Palm et al. have indicated, countries should not simply avoid fertilizers for environmental reasons, since soil degradation induced by fertilizer omission poses much a greater risk to agricultural production. A second class of concerns focuses on inequality and the potential scale bias of modern inputs. Hayami and Ruttan review the evidence on the alleged scale bias in the Asian green revolution and find that the evidence does not support this allegation. A third set of concerns focuses on both the challenges of governments implementing input support programs and also the challenges of exiting from them in due course. Though there is evidence that subsidy programs can be successful , there is also evidence that they can be subject to elite capture, and there is concern that their fiscal drag effects can far outlive their usefulness . While our results provide some evidence for a causal link from agricultural productivity increases to structural change and higher non-agricultural labor productivity, we can only speculate on the mechanisms through which these effects play out. Nevertheless, our novel identification of a causal link from yield increases to labor composition shift and non-agricultural productivity increases rules out models where structural change is driven solely by “pull” forces from growing non-agricultural sectors. To the extent that our results show that yield increases contribute to increases in non-agricultural labor productivity growth, this suggests that structural change involves more than just the satiation of food needs and the movement of labor into other sectors. This labor share shift somehow accelerates labor productivity growth. One possible mechanism might be increasing returns in the non-agricultural sector, perhaps through learning-by-doing as in the example modeled in Section 2 of this paper. Perhaps increased food production lowers average prices and frees up consumers’ resources for other consumption and for productive public and private investments, raising labor productivity elsewhere. Or perhaps higher availability of staple foods promotes improved health and labor productivity across sectors. Identifying more precise causal pathways between staple yields and structural change forms an important topic for future work.

Karadimou and Markatos developed a transient two-phase model to study particle distribution in the indoor environment using Large Eddy Simulation method. Baek et al. used CFD analysis to study various combinations of air conditioners and fans to improve growth rate in a plant factory. More recently, Niam et al. performed numerical investigation and determined the optimum position of air conditioners in a small vertical plant factory is over the top. In addition, a variety of mathematical techniques are proposed to provide sub-model for investigating photosynthesis. According to Boulard et al., tall canopies can induce a stronger cooling of the interior air by using a CFD model to study the water vapor, temperature, and CO2 distribution in a Venlo-type semi-closed glass greenhouse. Despite the fact that photosynthesis plays an integral role in distribution of species and uniformity along cultivation trays, this issue has not been well addressed. Although numerous research works have been done to investigate the turbulent flow in enclosures and buildings, this study is the first to numerically investigate the transport phenomena considering the product generation and reactant consumption through photosynthesis and plants transpiration with CFD simulations for IVFS-based studies. Furthermore, a newly proposed objective uniformity parameter is defined to quantify velocity uniformity for individual cultivation trays. Moreover, numerical simulations are performed to simulate and optimize fluid flow and heat transfer in an IVFS for eight distinct placements of flow inlets and outlets in this study. Accordingly, the effects of each case on uniformity, relative humidity, temperature,strawberry gutter system and carbon dioxide concentration are discussed in detail. Finally, an overall efficiency parameter is defined to provide a holistic comparison of all parameters and their uniformity of each case.In this study, three-dimensional modeling of conjugated fluid flow and heat transfer is performed to simulate the turbulent flow inside a culture room having four towers for hydroponic lettuce growth. Assuming that the four towers are symmetric, a quarter of the room with four cultivation trays is selected as the computational domain, as illustrated in Fig. 1a.The effect of LED lights on heat transfer is considered through constant heat flux boundary conditions at the bottom surface of each tray as shown in Fig. 1b. Lastly, the species transfer due to photosynthesis are occurring only in the exchange zone, which is illustrated in Fig. 1c. To study the impact of air inlet/exit locations on characteristics of air flow, four square areas, denoted as A, B, C, and D in Fig. 1a, are considered to be inlet, exit, or wall. To perform a systematic study, Table 1 presents the location of inlet and exit for all eight cases studied. With the aim of comparing all of the proposed designs, case AB is selected to be the baseline.To consider the effect of heat transfer with the outdoor ambient air, a solid wall zone comprised of plywood with a thickness of 0.12 m is assumed in the simulation. A constant-temperature boundary condition is set on the outer surface of the wall. Both conduction and convective heat transfer are considered within the model. All dimensions and boundary conditions are listed in Table 2.

In our model, the species exchange zone of photosynthesis is defined to be directly above the upper surface of each tray. These zones have the same cross-sectional area as the trays with the height of 0.1 m. Within the exchange zone, the water transpiration rate and carbon dioxide consumption rate are defined according to the experimental data obtained by Jin et al.and Adeyemi et al..One of the most critical factors affecting crop growth rate is the air flow velocity over plants. A fluid stream with horizontal speed ranging from 0.3 to 0.5 m s−1 can escalate the species exchange between the flow and plant leaves resulting in enhancement of photosynthesis. In indoor farming systems, the flow velocity can be controlled well using ventilation fans for more efficient plant growth. However, heterogeneous distribution of feeding air over plant trays can cause undesirable non-uniformity in crop production, which should be avoided. Therefore, it is important to study the effect of inlet-outlet location and flow rate on the flow patterns throughout the culture room. Herein, the most favorable condition is defined as the condition at which the flow velocity above all trays is equal to the optimum speed Uo, which is set to be 0.4 m s−1. The objective uniformity, OU, defined in Eq. is used to assess the overall flow conditions. The OU for all eight cases as a function of mass flow rate are summarized in Fig. 5. Since the inlet/exit area and air density remain the same, the mass flow rate is directly proportional to flow velocity. In addition, the target flow velocity over the plants is set to be 0.4 m s−1. Therefore, a general trend of OU first increases and then decreases when increasing the overall mass flow rate. Depending on the design, the peak of OU occurs at different mass flow rate for each case. Another general trend can be observed that the peak of OU occurs at a lower mass flow rate if the inlet is located at the top due to buoyancy force. This can be clearly demonstrated by cases AB and BA or AD and DA . Therefore, there exists a different optimal inlet/exit design for each mass flow rate condition. As can be seen from Fig. 5, the maximum OU at flow rates of 0.2, 0.3, 0.4 and 0.5 kg s−1 is observed for configurations AD, BC, BA, and DA, respectively. Therefore, this simulation model can identify optimal flow configuration at a specific mass flow rate condition.

Research over the past 2 decades has shown that seasonally flooded lands support a suite of native fishes and provide food web subsidies within and to downstream habitats . At the same time, these studies have shown that the Yolo Bypass is far from optimal habitat because the landscape has been altered to drain relatively quickly, and is often disconnected from the Sacramento River by levees and weirs that create major passage problems for upstream migrating adult fishes, such as Chinook Salmon and sturgeon . Several of these issues will be addressed in coming years by proposed structural changes to Fremont Weir at the upstream end of Yolo Bypass, and by the additional improvements to the floodplain’s water distribution system . However, the question remains whether changes to agricultural land management and infrastructure can provide reliable fish habitat that can increase the growth and survival of juvenile native fishes, and thereby contribute to reversing their overall decline, aid in the recovery of native fishes listed under the U.S. and California Endangered Species acts, and increase the availability of fishery resources. To help the overarching objective of providing reliable fish habitat, our team conducted a series of field studies during 2012-2017. To test fish and food web responses within different land-management scenarios, we conducted our project on standard rice and winter wheat fields, adjacent fallow lands, and rice fields with different harvest practices or other experimental modifications. This work yielded several publications that provided insight into habitat conditions in flooded rice fields for fish and invertebrates . The focus of our effort was on rearing habitat for young Chinook Salmon, but this work may also be relevant to other native fishes. The goal of this paper is to summarize the key lessons learned from 6 years of research on the feasibility of using farm fields as rearing habitat for juvenile Chinook Salmon in the Yolo Bypass and other Central Valley locations. Our hope is that our summary will provide guidance to future researchers, as well as inform managers as they evaluate potential management approaches. An important caveat is that our studies were not intended as a proof of concept for any specific management actions. Rather, our research was intended to examine some of the attributes that could reduce limitations to rearing conditions identified in early research,hydroponic grow table and gain insight into some of the key considerations for potential future agricultural floodplain management.

A second major caveat is that we had to rely on juvenile hatchery Chinook Salmon as a surrogate for wild Chinook Salmon, our ultimate target for habitat restoration. We recognize that there are several potential differences in the behavior of hatchery and wild Chinook Salmon . However, hatchery salmon were the only feasible alternative in this case since downstream migrating wild juvenile Chinook Salmon were mostly cut off from the Yolo Bypass because of extreme drought conditions. Nonetheless, hatchery salmon have been used successfully as a research tool in many types of ecological studies, so many of the lessons learned here should have at least some relevance to wild Sacramento River Chinook Salmon. Finally, our project was separate from a number of other fish management research projects in agricultural parcels, such as current efforts to investigate whether invertebrates grown on flooded rice fields can be used as a food subsidy for adjacent river channels . Previous research has shown that inundated Yolo Bypass floodplain habitat typically has substantially higher densities of phytoplankton, zooplankton, and drift invertebrates than the adjacent Sacramento River across a suite of water year types . Our studies consistently showed that managed inundation of agricultural fields supported statistically higher levels of phytoplankton and invertebrates than the Sacramento River . Also notable was that phytoplankton and zooplankton densities in our flooded experimental fields in Yolo Bypass were higher than those measured during river inundated flood events and in the Toe Drain, a perennial tidal channel . In addition, the invertebrate community in flooded rice fields was completely dominated by zooplankton , particularly Cladocera, whereas drift invertebrates such as Diptera were found in higher concentrations in study sites at Conaway Ranch and Dos Rios. Drift invertebrates are often a more substantial part of the food web in natural flood events in Yolo Bypass . Nonetheless, zooplankton densities can be relatively high in Yolo Bypass during dry seasons and drought years . The specific reasons for these differences include longer residence time and shallower depths in the Yolo Bypass than in adjacent perennial river channels.

Water source also may have been important for quantity and composition of invertebrates, including zooplankton, since all the managed flooding work was conducted using water from Knights Landing Ridge Cut, not the Sacramento River.Given the high densities of prey in the flooded fields, along with the low metabolic costs of maintaining position in a relatively low-velocity environment, it is not surprising that growth rates of juvenile salmon were comparatively high . This result was consistent across approaches used: cages, enclosures open to the substrate, and free-swimming fish. When cages were used, salmon were PIT tagged to track individual fish growth rates within a specific habitat. We consistently found that salmon growth rates in cages placed in flooded in rice fields were higher than growth rates for juvenile Chinook Salmon of comparative life stage in any of the adjacent riverine habitats and in other regions . Growth rates were also comparatively high when free-swimming salmon were introduced into larger-scale, 0.8-ha flooded agricultural fields. These studies were more representative than those using cages of how migrating salmon might use these habitats under natural flow events. For the multiple years that free-swimming salmon were used , they averaged a mean daily growth rate of 0.98mm d−1. Throughout all study years, caged salmon and free-swimming salmon showed very similar growth rates within the same experimental study units, despite the fact that they likely experienced different micro-habitat conditions . This observation suggests that our salmon growth results were not influenced by cage effects, a well-known issue in enclosure studies . To better understand managed floodplain processes across the region, in 2015, salmon were introduced in fields at a variety of locations in the Central Valley with various vegetative substrates: Sutter Bypass , three locations on the Yolo Bypass , and Dos Rios Ranch at the confluence of the Tuolumne and San Joaquin rivers . At all of the locations, juvenile Chinook Salmon grew at rates similar to those observed in experiments conducted at Knaggs Ranch in the Yolo Bypass during previous study years. These results suggest that multiple geographical regions and substrate types can support high growth rates of juvenile Chinook Salmon.

Throughout the 2012–2016 study period, we consistently observed that juvenile Chinook Salmon were attracted to sources of inflow, and that this sometimes became the dominant factor in the distribution of salmon on experimental fields or in enclosures. In the previously described PITtag observations in 2013, salmon in both enclosures positioned themselves nearest the inflow, regardless of surrounding habitat structure . This result is not surprising, given that juvenile stream salmonids commonly adopt and defend flow oriented positions in stream environments for acquisition of drifting food resources. On flooded agricultural fields, this orientation toward flow may not only be related to feeding behavior but may also serve to keep juvenile salmon in habitat areas that are hydrologically connected and have higher velocities. In fact, analyses of the environmental factors that predict movement of large groups of tagged juvenile Chinook Salmon in the Yolo Bypass found that drainage of flooded areas was a reliable predictor of fish emigration at downstream trapping stations . Although juvenile Chinook Salmon growth rates were consistently high across substrates and study years, we observed highly variable survival of salmon, and available evidence from the studies suggests that this was related, at least in part, to differences among years in drainage rates of the study fields and habitat availability on the floodplain at large. For example, survival in 2013 ranged from 0.0% to 29.3% in the replicated fields containing different agricultural substrates. This variability was likely unrelated to substrate type; instead, these low survival rates were most likely a result of very dry conditions across Yolo Bypass and the Central Valley, generally, when record drought conditions prevailed during 2012–2015, which affected water quantity and quality. In 2013, our replicated field study likely presented one of the only wetted floodplain areas for miles around, and thus presented a prime feeding opportunity for avian predators such as cormorants, herons, and egrets. However, when the same set of fields was used in 2016, survival was much higher . This was generally a wetter period, avian predation pressure was reduced, and we more efficiently opened the flash boards to facilitate faster drainage and fish emigration. Note, however, there were some differences in methodology among years, which may have contributed to survival variability. Taken together, these observations of free swimming salmon survival suggest that field drainage rate, and overall floodplain habitat availability,flood tray are important factors for improving survival in managed agricultural floodplain habitats. Our observations of juvenile salmon orientation to flow, and the importance of efficient drainage on survival, reinforce observations from natural floodplains that connectivity between perennial channel habitat and seasonal floodplain habitat is an essential attribute of river-floodplain systems . Connectivity of managed floodplain habitats to unmanaged habitats in the river and floodplain is therefore a foundational condition needed to allow volitional migration of juvenile salmon. Further research is needed to identify how to provide sufficient connectivity to maximize rearing and migration opportunities for wild Chinook Salmon.

Natural and managed floodplain habitat is subject to a variety of flow and environmental conditions. Variation in flow and temperature dictates when and where managed agricultural habitats may be accessible and suitable for rearing salmonids, with challenges during both wet and dry years, as well as during warm periods. As noted previously, survival in the replicated fields was variable but generally low. We associate these results with the effects of extreme drought conditions that prevailed during the core of our study from 2012 through 2015. Although our field studies were conducted during a time of year when wild salmon have historically used the Yolo Bypass floodplain , the extreme drought made for warm water temperatures, and resulted in our study site being one of the few inundated wetland locations in the region. As such, avian predators were attracted to the experimental fields, exacerbating salmon mortality during drainage. We observed high concentrations of cormorants, herons, and egrets on the experimental fields, and this concentration increased over the study period. As many as 51 wading birds and 23 cormorants were noted during a single survey.This situation highlights the importance of the weather dependent, regional context of environmental conditions, which govern how and when managed floodplains can be beneficial rearing habitats for juvenile salmon. Under certain circumstances, flooded fields can generate high salmon growth but in other scenarios, these habitats can provide poor environmental conditions for salmonids and/or become predation hot spots. Even during wetter conditions, we found that management of agricultural floodplain habitat was challenging. For example, we had hoped to test the idea of using rice field infrastructure to extend the duration of Yolo Bypass inundation events in an attempt to approximate the longer-duration events of more natural floodplains; that is, through flood extension. As noted by Takata et al. , use of the Yolo Bypass by wild Chinook Salmon is strongly tied to hydrology, and salmon quickly leave river-inundated floodplains once drainage begins. We therefore reasoned that flooded rice fields might provide an opportunity to extend the duration of flooding beyond the typical Yolo Bypass hydrograph. In 2015, a flood extension study was planned but not conducted because drought conditions precluded Sacramento River inflow via Fremont Weir. To test the flood extension concept in 2016, we needed substantial landowner cooperation and assistance to install draining structures that allowed maintenance of local flooding after high flow events. Even then, we found it difficult to maintain water levels and field integrity during the tests. In our case, we were fortunate to have the cooperation of willing landowners. Partnership with landowners was key, and would be critical with any future efforts to test the concept of flood extension. We also planned a similar test in 2017, but high and long-duration flood flows prevented the study from occurring.

Although the same levels of data collection and precision application of inputs are not likely to be widely used in resource-poor farming situations, advances in technologies are likely to provide additional options in those regions.For example, the Global Open Data for Agriculture and Nutrition initiative is promoting global efforts to make agricultural and nutritionally relevant data available, accessible, and usable for unrestricted use worldwide . There are over 150 partners in this initiative from national governments, non-governmental, international and private sector organizations who support this effort. It is clear that there is a need for a more focused effort to connect the various agricultural systems modeling, database, data harmonization, open-access, and DSS efforts together, so that the scientific resources being invested in these different initiatives will contribute to compatible set of models, data, and platforms to ensure global public goods. This is critically important, considering that these tools are increasingly needed to ensure that agriculture will meet the food demands of the next 50 to 100 years and will be sustainable environmentally and economically. Efforts are underway to remedy this situation by a number of groups . Moreover, as detailed in Antle et al. , there is a need for strategies such as private-public partnerships to bring together the power of private sector investments with the ongoing research to advance models and modeling tools. This is true for production models of crops and animals as well as economic models across each of the first three Use Cases that address issues in data-poor areas in Sub Saharan Africa. Finally, based on the current status of models, data, and knowledge systems, a strategy should include the appropriate modification and in some cases re-programming of existing component models that already include many needed capabilities. This would facilitate extension of components that respond to factors that are not currently considered by models, using a range of methods including statistical models,vertical rack system reduced form models, extended databases, and modular models that integrate component sub-modules. Seavert et al. suggested that some data limitations could be overcome by integrating farm-level models and knowledge products with landscape-scale data and models.

Recent experience in AgMIP demonstrated the value of multiple models indicating that it would not be useful to pursue a goal of producing perfect models for crops, livestock, and farming systems. Although there are excellent prospects for considerable advances in agricultural systems data, models, and knowledge systems, there are inherent limitations in these tools due to irreducible uncertainties in model structures, spatial variability of physical, chemical, genetic, and socioeconomic conditions. These limitations will continue to vary depending on applications, which suggest that future evaluation of capabilities and limitations should be based on well-defined Use Cases. This review indicates that the current state of agricultural systems models is sufficient for some contemporary applications, but that major advances are needed to achieve the next generation of data, models, and knowledge systems to address more complex issues and achieve food security during the next century.Farmers and other agricultural stakeholders are experimenting with many types of information and communication technology such as websites, blogs, social media and mobile decision support applications. As data scientists integrate ICT with “big” data, farmers can downscale diverse sets of information for local decision-making and upscale local data to see emergent patterns at multiple scales. Social media tools allow extension professionals, farmers and other agricultural stakeholders to communicate in new ways about the broad range of issues affecting agroecological systems. The increasing use of ICT in agriculture has engendered a significant debate about its benefits for achieving extension goals relative to its potential risks and costs. This paper empirically examines ICT use among extension professionals working on sustainable agriculture in California. We broadly define “extension professionals” as professionals engaged in agriculture outreach and extension, either based at a university or elsewhere throughout the food system and agricultural knowledge networks . We particularly emphasize the role of social media platforms such as Twitter, Facebook and LinkedIn as innovative extension tools for building knowledge networks, coordination, communication, outreach and education. We draw on diffusion of innovation theory as a framework that can integrate many elements of the debate about the benefits and risks of ICT . Diffusion of innovation theory suggests that ICT adoption depends on how extension professionals perceive the attributes of this innovative technology, such as its relative advantage over other extension tools and its complexity. We also examine how demographic characteristics of extension professionals influence ICT adoption. Our analysis sheds light on the potential technology gap, hinted at by extant research, between extension professionals’ use of ICT and the general public’s, and possibly agricultural clientele’s, greater use of ICT.

Developing policy recommendations to improve the appropriate use of ICT requires identifying the critical barriers to ICT adoption among extension professionals. Our research has implications for broader ideas about how to adapt extension systems to the new realities of agricultural knowledge networks and innovation systems . Modern agricultural knowledge networks are distributed systems, where relevant information is developed and communicated by a wide range of stakeholders. The traditional top-down model of delivering land grant university research to local clientele is becoming obsolete, especially when resources are thin . It must be complemented by a more bottom-up model, where in addition to developing and broadcasting new knowledge, land-grant universities and other extension organizations must build innovation systems that coordinate knowledge networks among different stakeholders . Such networks seek to synergistically combine social, technical and experiential learning. New ICTs are potentially important tools in this endeavor, especially when used to complement other methods of outreach and education. The results of this paper enhance the evidence base for this endeavor. The information technology revolution has transformed the way that people access information and build social connections across the globe. The latest survey results from the Pew Research Center estimated that the percentage of U.S. citizens using at least one social media site increased from 5% in 2005 to 69% in 2016. Social media use was more frequent among women and individuals in higher education and income categories. In 2016, Facebook had the highest market share , followed by Instagram , Pinterest , LinkedIn and Twitter . Farmers are increasingly connected but lag behind the general population. USDA NASS estimated that in 2017 more than 70% of farmers in the United States had computer and internet access and 47% used computers for farm business. Computer and internet usage was higher among wealthy farmers. A study in the Pacific Northwest found that potato growers used popular ICT platforms as frequently as college students — 93% of growers used email compared with 97% of students; 97% of growers used text messages compared with 94% of students; 70% of growers used Facebook compared with 73% of students; and 90% of growers used YouTube compared with 91% of students — and growers overall used 3.5 more varieties of technology than college students. In developing countries, mobile phone technology continues to expand and provides a crucial information and networking resource for rural agricultural populations . Despite some evidence that extension clientele are using ICT at rates approaching those of the general population, extension professionals may be lagging behind both groups. Gharis et al. reported that among participants in a Natural Resources Conservation Service webinar, 53% used Facebook and 10% used Twitter. O’Neill et al. found that the proportion of members of the financial services community of practice for e-Extension using Facebook or Twitter daily is far less than the general population. While the existing research hints at a potential technology gap in extension professionals’ use of ICT, much more research is needed to document and explain ICT adoption and use within agricultural systems. The potential gap in extension professionals’ use of ICT reflects a lively ongoing debate about the costs, benefits, barriers and risks of ICT for agriculture . On the benefits side, ICT may provide access to information, coordination, job opportunities, social networks and improved services . Extension professionals expect ICT to create a snowball effect , with information more quickly reaching a larger and more diverse audience than in person communication methods like workshops and field meetings . The benefits may include the integration of real-time information into mobile applications or websites to provide decision support, linking daily agricultural decisions to economic and agro-ecological processes at multiple scales. Realizing these benefits requires overcoming many potential risks,mobile grow rack barriers and costs. Gadino et al. highlighted the importance of linking traditional in person methods with digital technology and the time required to update ICT with new and real-time information. Newbury et al. identified the barriers as lack of training, concern about information control and time availability.

Gharis et al. emphasize lack of professional acceptance by colleagues as a barrier to innovation, which is linked to the capacity to measure effectiveness. O’Neill et al. pointed out the need for organizational procedures; only 29% said their institutions had guidelines for reporting, and only 22% of their respondents reported their own social media outreach activities to their extension administration. There was a notable amount of uncertainty — 27% of non-reporters said they did not know how to use social media, and 38% did not know if their institution had guidelines.Existing research lacks a theoretical framework to integrate the diverse terms of the debate about ICT adoption among extension professionals. Diffusion of innovation theory, which examines how innovations spread through a population of users, provides such a framework. It has been an enduring research topic in agricultural decision-making for more than a century . A central argument of diffusion theory is that the likelihood of an innovation being adopted is related to the following attributes of the innovation: relative advantage, compatibility, complexity, trialability and observability. We used these attributes to frame our research hypotheses. “Relative advantage” refers to the innovation’s potential benefits and opportunities relative to other extension tools. For ICT, the most frequently discussed advantages are its capacity to reach larger, more diverse and more geographically dispersed audiences . Also, ICT can quickly deliver new information, potentially in real time with linkages to large-scale data. ICT may also provide support for on-the-ground decisions, for example, about agriculture management, or for coordinating the activities of extension professionals. “Compatibility” is the extent to which the innovation is compatible with professional and social norms. For extension, an important norm is delivering scientifically valid and neutral information to support decision-making and stakeholder dialogue. Especially with the everyday mention of “fake news” and “internet trolls,” extension professionals worry that social media may facilitate the spread of misinformation and provide an avenue for unreasonable individuals to corrode civic dialogue. In addition, many extension professionals feel that relative to more traditional outreach and publication strategies, there is a lack of professional incentives and peer recognition for the use of ICT. “Complexity” refers to the difficulties of integrating the innovation. In terms of the ICT debate, not all extension professionals have the technical knowledge to effectively use social media platforms or effectively integrate communication across multiple platforms. It may take too much time to learn how to use social media and maintain an active web presence. These complexities are exacerbated by a lack of widely recognized best practices about how to effectively craft social media communication. “Observability” and “trialability” refer to the extent to which the innovation’s effectiveness can be observed and tracked. There is a lack of clarity about how to track the effectiveness of ICT, for example, observing who accesses and uptakes information posted on Facebook or Twitter . This includes the use of altmetrics, since there is no universally accepted method of measuring social media effectiveness and no clear policies from the University of California, UC Agriculture and Natural Resources, or other organizations. Furthermore, it is more difficult to control access to or target the audience for social media information with the same precision as in-person strategies aimed at particular constituencies. We studied ICT use among extension professionals involved in sustainable agriculture in California. An empirical study, it analyzed whether ICT adoption and use was affected by perceptions about ICT and the professional demographics of the individual user.

Holzworth et al. discussed advances in capabilities and applications over time. Basso et al. reviewed the performance of CERES maize , wheat and rice models compared to measured data over the last 30 years in 43 countries. They reported that model performance, using site-specific inputs, was outstanding for the variables compared . Models of cropping and grassland systems share the same fundament characteristics: both describe crop or grassland agro-ecosystem growth and yield responses to climate, soil, plant species characteristics, and management. However, several aspects of grassland/rangeland modeling present unique challenges. Many of these challenges stem from the requirement that grassland models represent several interacting species, including perennial and woody species of grasses. Persistence of plants over multiple years forces the models to consider residual effects over time. Dependency on soil-derived nutrients or human-induced disturbances like fire reinforce the longer-term perspective needed for grassland modeling. Thus, although most biophysical processes are similar additional factors are considered when modeling grasslands. 2.1.1. Model-simulated responses of interest to users The most common response variable modeled for cropping systems is yield, whether of grain, tuber, or forage biomass yield. This yield is harvested at a single point in time for determinate annual crops, while indeterminate crops and grasslands may be harvested multiple times. Although statistical models may be useful for predicting these biological yields in response to some combination of weather conditions, nutrient levels, irrigation amounts, etc. , they do not predict responses to non-linearities and threshold effects outside the range of conditions in data used to develop them. In contrast, dynamic cropping and grassland system models may simulate these biological yields and other responses important to analysts, such as crop water use, nitrogen uptake, nitrate leaching, soil erosion, soil carbon, greenhouse gas emissions,stackable planters and residual soil nutrients.

Dynamic models can also be used to estimate responses in places and for time periods and conditions for which there are no prior experiments. They can be used to simulate experiments and estimate responses that allow users to evaluate economic and environmental trade offs among alternative systems. Simulation experiments can predict responses to various climate and soil conditions, genetics, and management factors that are represented in the model. “Hybrid” agricultural system models that combine dynamic crop simulations with appropriate economic models can simulate policy-relevant “treatment effects” in an experimental design of climate impact and adaptation .One innovation of early crop modeling pioneers was to categorize the crop production situation being modeled to narrow down the many factors that are needed by crop models . Fig. 1 summarizes three crop production levels and factors that influence each. Potential production is defined as crop production that is determined completely by defining factors of CO2, radiation, temperature, and crop characteristics . Potential production models also include partitioning of biomass growth into grain and other plant parts, with defining factors modeled to affect these processes. This potential production level is rarely achieved in real production situations, although under highly intensive management , production approximates the potential level for the specific CO2, temperature, radiation, genetics, and canopy architecture used. For example, crops grown in greenhouses or in intensively managed fields in some regions produce yields that are at or near potential levels. The next production situation is referred to as water-limited and/or nutrient-limited production . At this level, the defining factors are still important, but there may also be limitations in the water and/ or nutrients needed to achieve full growth potential. Crop models that simulate water and/or nutrient-limitations must include soil water and nutrient component modules to simulate the time-varying availability of water and nutrients, the uptake of these resources, and reductions in growth and development if they are not adequate to meet potential growth demands.

Most cropping and grassland system models contain component modules that simulate soil water, nitrogen, and carbon dynamics because of the global importance of these resources in determining yield. Although some models include phosphorus, most of them do not simulate responses to phosphorus, potassium, or micro-nutrients. Models that represent soil water, nitrogen and carbon dynamics are complicated not only because of the physical and chemical processes that occur in soils, but also because of the complexities in management practices used for these resources . Finally, actual production includes additional factors that may reduce growth and yield . Whereas some crop models have capabilities to introduce damage by diseases and insects , the modeling of these reducing factors has not kept up with other advances in crop modeling for a review of recent progress. Most groups modeling cropping and grassland systems do not include these factors. Thus, few current models simulate responses to pest or disease damage or to their management using resistant varieties, agro-chemicals, or other approaches. This is a major limitation for some applications.Dynamic crop models generally include factors at the potential yield level in addition to water- and nitrogen-limited production level. However, the ways that different models include those factors vary. Fig. 2 shows a schematic of the components in the Cropping System Model that incorporates the CERES , CROPGRO, and other models in DSSAT . The CSM models can include soil water, nitrogen, carbon, and phosphorus dynamics and can introduce pest and disease damage into some crops using the concept of coupling points . It also can simulate multiple seasons so that carry-over changes in soil water, N, and P are simulated to represent longer-term changes in soil resources in response to different management systems . A number of other cropping and grassland system models have similar components and capabilities , although most models do not simulate impacts of pests and diseases unless coupled externally with time-series input data or pest models like in DSSAT CSM . Some models have an ability to simulate intercropping .

An unfortunate feature of current crop and grassland models is that modules from one set of models are not compatible with other models. For example, APSIM’s intercropping capabilities are deeply embedded in the system architecture and cannot be simply moved to other models like DSSAT CSM. Moving pest and disease damage modules from DSSAT CSM to APSIM is possible but requires coding of module “wrappers” to handle inter-model communications – a non-trivial task.Most “cropping system” models have evolved as elaborations of component crop and soil models and the focus has been on modeling a single “point” in space over time to explore variability in crop responses to soil, management and weather. A typical structure for this pedigree is shown in Fig. 2. Most operate on daily or hourly time-steps. Some include hourly time steps for computing rates of photosynthesis and other processes but also use daily steps to update state variables such as phenological development, and biomass of plant organs. These time steps are also used to compute changes in soil water, soil nitrogen, and crop biomass that result from soil-water processes including rainfall, infiltration, runoff, percolation, redistribution, and plant uptake, and changes in soil nitrogen. Details of how different growth, hydrology, and soil nutrient processes are represented vary among models. Models may be either functional or mechanistic, with the choice of approach depending on the modeling team’s knowledge of the system, their purpose, the availability of data for parameterization, and their experience in developing and evaluating models. These differences lead to different models producing different responses when used to simulate the same experiment . Most models use simplified functional equations and logic to partition simulated biomass into various plant organs. Functional models also primarily use “capacity” concepts to describe the amount of water stored in a soil that is available to plants; mechanistic models, in contrast, use the potential energy of soil water and “instantaneous rate” concepts from soil physics. In capacity-based functional models, it is the difference between the upper and lower limits of soil water-holding capacity that determine the amount of water available to plants. In this type of soil water model, water movement and its availability for crop growth are represented by functional equations on a daily time step, even though infiltration and runoff processes may be computed with smaller time steps. Some modeling systems can operate with either capacity based or energy based soil water modules and ideally a flexible agro-ecosystem simulation engine or platform will be able to work with component modules specified to different degrees of “mechanism”. Although some models include input information on plant genetics ,stacking pots these are few in number and not yet in widespread use. Most models are not genetic-based, which is one reason that calibration of models using field data is widely practiced to obtain genotype-specific parameters. Some modeling platforms while utilizing crop and soil components such as shown in Fig. 2, have focused more strongly on “agricultural system” features, with capabilities of instantiation that facilitates the simulation of systems features such as multiple paddocks, intercropping, weeds, tree – crop interactions, livestock operations and even non-biological features of farms such as water storage structures.

APSIM is the best known example of this farming systems “platform”. It sits at the interface of the crop-soil systems models typified by Fig. 2 and the whole farm optimization models discussed elsewhere in this paper. Holzworth et al. outlines in full these “agricultural systems” features of the APSIM approach .Grasslands are usually mixed stands comprised of a variety of grasses and forbs, including legumes and sometimes woody species . Unlike croplands, the diversity of species generally precludes use of a single-species parameterization, since species vary in their ability to compete for space, water, nutrients , and light. Grassland models generally represent plant behavior and competition among herbaceous plants using one of: a set of species, each independently parameterized; amalgamations of plants into parameters for plant functional types ; or community-averaged parameterizations . While requiring more effort for parameterization, these amalgamated approaches enable representation of changes in plant community composition over time, for example in response to climate change, competition among plant populations, and mortality. Trees are dynamic components of the world’s native grazing lands and can have significant impacts on ecosystem function . Representing tree/grass competition is challenging because trees respond differently to various drivers and depend on plant population characteristics . Shifts in plant community composition can be self-reinforcing due to co-occurring population and biophysical changes . Dynamic vegetation modeling approaches are used to represent competition among herbaceous and woody types for water, nitrogen, light, and space. Dynamic rangeland vegetation models and state-and-transition models identify a set of plant communities that tend to resist change due to disturbance, but also describe drivers that lead to a transition to another quasi-stable plant community . Expansion of woody species and increases in woody cover are widespread phenomena that under many but not all environmental conditions lead to the transition of early successional communities dominated by grasses and forbs to forests . Studying woody encroachment and understanding the importance of competing drivers has been challenging, in part because of the slow rates of the processes driving changes . These slow changes are reflected in the drivers of transitions in state-and-transition models and contribute to uncertainty in our ability to represent longer-term changes in the tree-grass balance. Ecological succession has been studied by plant ecologists since pioneering work before 1945. More interactions among agricultural and ecological modelers are likely to be mutually beneficial. Grazing animals of all kinds have an impact on plant productivity by removing photosynthesizing tissues, altering light transmission through the canopy, influencing nutrient cycling and affecting plant allocation patterns and differentially influencing species mortality and recruitment rates in grasslands . Such changes to groups of plants can drive changes in the competitive balance and thus plant community composition. Whereas grassland models incorporating species or plant functional types can represent grazing-induced changes in the competitive balance, such models that represent plants with a set of community-wide parameters usually rely on some combination of LAI -driven reduction in production potential along with grazing response curves. Ingrasslands/rangelands, grazing removes some plant productive capacity, and thus models cannot rely upon deterministic growth curves, but must be able to forecast growth for plants with an amount of biomass or leaf area that varies independent of the time of year or climate. There can also be significant differences in growth rates among and even within species after a grazing event .